Nothing
context("Negative values and reduce = FALSE")
test_that("Symmetry", {
data("darfur")
library(sensemakr)
darfur2 <- darfur
darfur2$directlyharmed <- darfur2$directlyharmed*(-1)
model <- fixest::feols(peacefactor ~ directlyharmed + age + farmer_dar + herder_dar +
pastvoted + hhsize_darfur + female + village, data = darfur)
model2 <- fixest::feols(peacefactor ~ directlyharmed + age + farmer_dar + herder_dar +
pastvoted + hhsize_darfur + female + village, data = darfur2)
sens1 <- sensemakr(model = model, treatment = "directlyharmed", q = 1)
sens2 <- sensemakr(model = model2, treatment = "directlyharmed", q = 1)
expect_equal(abs(sens1$sensitivity_stats[-1]), abs(sens2$sensitivity_stats[-1]))
sens3 <- sensemakr(model = model, treatment = "directlyharmed", q = 1, reduce = F)
sens4 <- sensemakr(model = model2, treatment = "directlyharmed", q = 1, reduce = F)
expect_equal(abs(sens3$sensitivity_stats[-1]), abs(sens1$sensitivity_stats[-1]))
expect_equal(abs(sens4$sensitivity_stats[-1]), abs(sens2$sensitivity_stats[-1]))
})
test_that("reduce = FALSE", {
data("darfur")
library(sensemakr)
darfur2 <- darfur
darfur2$directlyharmed <- darfur2$directlyharmed*(-1)
model <- fixest::feols(peacefactor ~ directlyharmed + age + farmer_dar + herder_dar +
pastvoted + hhsize_darfur + female + village, data = darfur)
sens1 <- sensemakr(model = model, treatment = "directlyharmed", q = 1)
sens2 <- sensemakr(model = model, treatment = "directlyharmed", q = 1, reduce = FALSE)
expect_true(sens1$sensitivity_stats$t_statistic > 0)
expect_true(sens2$sensitivity_stats$t_statistic < 0 )
expect_equal(abs(sens1$sensitivity_stats[-1]), abs(sens2$sensitivity_stats[-1]))
sens1 <- sensemakr(model = model, treatment = "directlyharmed", q = 2, benchmark_covariates = "female", kd = 1:3)
sens2 <- sensemakr(model = model, treatment = "directlyharmed", q = 2, benchmark_covariates = "female", kd = 1:3, reduce = FALSE)
h01 <- attr(sens1$bounds$adjusted_t, "h0")
h02 <- attr(sens2$bounds$adjusted_t, "h0")
expect_equal(h01, sens1$sensitivity_stats$estimate*(1-2))
expect_equal(h02, sens1$sensitivity_stats$estimate*(1+2))
expect_true(sens2$sensitivity_stats$t_statistic < 0 )
expect_equal(abs(sens1$sensitivity_stats[-1]), abs(sens2$sensitivity_stats[-1]))
ts <- with(sens1$bounds, (adjusted_estimate-h01)/adjusted_se)
expect_equivalent(ts, sens1$bounds$adjusted_t)
})
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